scholarly journals A State-Space Model of an Inverter-Based Microgrid for Multivariable Feedback Control Analysis and Design

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3279
Author(s):  
Juan F. Patarroyo-Montenegro ◽  
Jesus D. Vasquez-Plaza ◽  
Fabio Andrade
Keyword(s):  
State Space ◽  
Control Strategies ◽  
State Space Model ◽  
Control Analysis ◽  
Control Methods ◽  
Linear Quadratic ◽  
Analysis And Design ◽  
Space Model ◽  
Bus Voltage ◽  
Multivariable Feedback

In this work, a synchronous model for grid-connected and islanded microgrids is presented. The grid-connected model is based on the premise that the reference frame is synchronized with the AC bus. The quadrature component of the AC bus voltage can be cancelled, which allows to express output power as a linear equation for nominal values in the AC bus amplitude voltage. The model for the islanded microgrid is developed by integrating all the inverter dynamics using a state-space model for the load currents. This model is presented in a comprehensive way such that it could be scalable to any number of inverter-based generators using inductor–capacitor–inductor (LCL) output filters. The use of these models allows designers to assess microgrid stability and robustness using modern control methods such as eigenvalue analysis and singular value diagrams. Both models were tested and validated in an experimental setup to demonstrate their accuracy in describing microgrid dynamics. In addition, three scenarios are presented: non-controlled model, Linear-Quadratic Integrator (LQI) power control, and Power-Voltage (PQ/Vdq) droop–boost controller. Experimental results demonstrate the effectiveness of the control strategies and the accuracy of the models to describe microgrid dynamics.

scholarly journals Model Predictive Control with a Relaxed Cost Function for Constrained Linear Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
David Sotelo ◽  
Antonio Favela-Contreras ◽  
Viacheslav V. Kalashnikov ◽  
Carlos Sotelo
Keyword(s):  
Model Predictive Control ◽  
Cost Function ◽  
State Space ◽  
Predictive Control ◽  
Discrete Time ◽  
Control Strategy ◽  
Control Strategies ◽  
State Space Model ◽  
Control Technique ◽  
Space Model

The Model Predictive Control technique is widely used for optimizing the performance of constrained multi-input multi-output processes. However, due to its mathematical complexity and heavy computation effort, it is mainly suitable in processes with slow dynamics. Based on the Exact Penalization Theorem, this paper presents a discrete-time state-space Model Predictive Control strategy with a relaxed performance index, where the constraints are implicitly defined in the weighting matrices, computed at each sampling time. The performance validation for the Model Predictive Control strategy with the proposed relaxed cost function uses the simulation of a tape transport system and a jet transport aircraft during cruise flight. Without affecting the tracking performance, numerical results show that the execution time is notably decreased compared with two well-known discrete-time state-space Model Predictive Control strategies. This makes the proposed Model Predictive Control mainly suitable for constrained multivariable processes with fast dynamics.

The Linear Optimal Control for the Mechanical Vibration Based on Remanufacturing Repaired

2013 ◽  
Vol 823 ◽  
pp. 47-51
Author(s):  
Ling Liu
Keyword(s):  
Optimal Control ◽  
State Space ◽  
Vibration Suppression ◽  
State Space Model ◽  
State Regulation ◽  
Order System ◽  
Modal Control ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Space Model

It is used by the piezoelectric ceramics sheet of positive-inverse piezoelectric effect in a set of copper alloy remanufacturing repair cantilever vibration system as the research object in the paper.A state space model have been generated on the cantilever beem mechanical structure of dynamics finite element modeling and degrees of freedom dynamic polycondensation.It is inhibited effectively when a cantilever beam subjected to external transient pulse disturbance caused by first order, two order and higher order system mode vibration,by using the linear quadratic optimal control of two state regulation for the detection of position feedback independent modal control on the basis of the state-space model. Software is used to simulate active vibration control effect.The simulation results show that the mode control inhibited have excellent effects for the repaired cantilever vibration, also analysed on the modal control parameters for the vibration suppression effect.

scholarly journals STEADY-STATE ANALYSIS AND DESIGN METHODOLOGY FOR CLASS-E² RESONANT DC/DC CONVERTERS BASED ON A NORMALIZED STATE-SPACE MODEL

2020 ◽  
Vol 25 (2) ◽  
pp. 209-218
Author(s):  
Lucas Sangoi Mendonça ◽  
João Pedro Scherer Cipriani ◽  
Thiago Cattani Naidon ◽  
Fábio Ecke Bisogno
Keyword(s):  
Steady State ◽  
State Space ◽  
Design Methodology ◽  
State Space Model ◽  
Steady State Analysis ◽  
Analysis And Design ◽  
Space Model ◽  
Class E ◽  
State Analysis

Multivariable modeling and control of an activated sludge process

1998 ◽  
Vol 37 (12) ◽  
pp. 149-156 ◽  
Author(s):  
Carl-Fredrik Lindberg
Keyword(s):  
Activated Sludge ◽  
Nitrate Concentration ◽  
State Space Model ◽  
Activated Sludge Process ◽  
Invariant State ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Space Model ◽  
And Control ◽  
Time Invariant

This paper contains two contributions. First it is shown, in a simulation study using the IAWQ model, that a linear multivariable time-invariant state-space model can be used to predict the ammonium and nitrate concentration in the last aerated zone in a pre-denitrifying activated sludge process. Secondly, using the estimated linear model, a multivariable linear quadratic (LQ) controller is designed and used to control the ammonium and nitrate concentration.

Development of L1-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

2021 ◽  
pp. 095965182199617
Author(s):  
Mahyar Akbari ◽  
Abdol Majid Khoshnood ◽  
Saied Irani
Keyword(s):  
Fault Detection ◽  
State Space ◽  
Gas Turbine ◽  
Sliding Mode ◽  
State Space Model ◽  
Sensor Fault ◽  
Space Model ◽  
Decision Logic ◽  
Sensor Fault Detection ◽  
Industrial Gas Turbine

In this article, a novel approach for model-based sensor fault detection and estimation of gas turbine is presented. The proposed method includes driving a state-space model of gas turbine, designing a novel L1-norm Lyapunov-based observer, and a decision logic which is based on bank of observers. The novel observer is designed using multiple Lyapunov functions based on L1-norm, reducing the estimation noise while increasing the accuracy. The L1-norm observer is similar to sliding mode observer in switching time. The proposed observer also acts as a low-pass filter, subsequently reducing estimation chattering. Since a bank of observers is required in model-based sensor fault detection, a bank of L1-norm observers is designed in this article. Corresponding to the use of the bank of observers, a two-step fault detection decision logic is developed. Furthermore, the proposed state-space model is a hybrid data-driven model which is divided into two models for steady-state and transient conditions, according to the nature of the gas turbine. The model is developed by applying a subspace algorithm to the real field data of SGT-600 (an industrial gas turbine). The proposed model was validated by applying to two other similar gas turbines with different ambient and operational conditions. The results of the proposed approach implementation demonstrate precise gas turbine sensor fault detection and estimation.

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